Publicerad: 2025-04-25
Postdoc in Safe, interpretable, learning-based motion planning and control
We invite applications for a postdoctoral researcher to join an interdisciplinary project aimed at advancing safe and transparent control for autonomous, over-actuated electric vehicles. This position is part of a collaborative effort between Chalmers University of Technology, Volvo Cars, and Volvo Group, and offers a unique opportunity to work at the intersection of control theory, machine learning, and vehicle technology.
The research addresses key challenges in motion planning and control under uncertainty, with a particular focus on how to allocate forces and make robust decisions when some vehicle actuators may be partially or fully degraded. You will contribute to both theoretical developments and applied solutions, with a strong emphasis on safety, interpretability, and real-time feasibility.
This is a stimulating position for candidates interested in interpretable AI, formal safety guarantees, and impactful research in sustainable mobility.
Project overview
The position focuses on interpretable, learning-based stochastic optimal control for over-actuated electric vehicles—vehicles with more actuators than degrees of freedom, which enable sophisticated control strategies but also increase system complexity.
Your work will include:
• Developing modular, efficient, and transparent control algorithms.
• Combining model predictive control with learning-based motion prediction under uncertainty.
• Ensuring algorithms can be deployed in real-time settings.
• Contributing to the development of open-source tools.
The project has both a strong theoretical foundation and practical relevance, aiming to deliver robust, explainable control methods that can be applied in real-world scenarios.
As a postdoc, you will also contribute to the academic environment through co-supervision of students, publication of results in high-impact journals and conferences, and participation in national and international research collaborations.
Research environment
You will be based at the Systems and Control Division at Chalmers, which conducts research in modelling, learning, and optimization for systems such as robots, autonomous vehicles, and electromobility solutions. The division offers a rich academic setting with strong expertise in control theory, machine learning, and probability.
You will also collaborate with:
• Vehicle Safety Division, which applies systems engineering and human factors to improve traffic safety. This division is internationally recognized for its work in virtual safety assessment and predictive evaluation of driver behavior and vehicle systems.
• Vehicle Engineering and Autonomous Systems (VEAS) Division, which conducts research in sustainable transportation, including vehicle dynamics, autonomous systems, and energy-efficient mobility solutions.
Together, these divisions create a dynamic and interdisciplinary environment with close ties to industry and society.
Main responsibilities
• Conduct high-quality research in interpretable, learning-based stochastic optimal control.
• Design and implement scalable algorithms for motion planning and control in uncertain environments.
• Collaborate with industry partners to validate methods via simulation and, potentially, real-world prototypes.
• Publish research results and present them at international venues.
• Engage in cross-disciplinary collaborations and contribute to the broader research community at Chalmers.
• Support the supervision of bachelor’s, master’s, and PhD students.
• Contribute to the preparation of research proposals and technical reports.
Your profile
To be eligible for this position, you must have:
• A PhD awarded no more than three years prior to the application deadline, in a relevant subject area such as control systems, robotics, applied mathematics, or machine learning.*
• Strong programming skills and experience with numerical methods and simulation.
• Excellent communication skills in English, both written and spoken.
• Demonstrated ability to work in international and cross-organizational research environments.
*Exceptions to the three-year rule may be granted for documented periods of parental leave, sick leave, or military service. The date on your doctoral certificate will be used to determine eligibility.
Contract terms
This postdoc position is a full-time temporary employment for two to three years.
What we offer
Chalmers provides a cultivating and inspiring working environment in the coastal city of Gothenburg.
Read more about working at Chalmers and our benefits for employees.
Application procedure
The application should be written in English and be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.
CV: (Please name the document as: CV, Surname) including:
• CV, include complete list of publications
• Previous teaching and pedagogical experiences
• Two references that we can contact.
Personal letter: (Please name the document as: Personal letter, Family name)
1-3 pages where you:
• Introduce yourself
• Describe your previous research fields and main research results
• Describe your future goals and future research focus
Other documents:
• Attested copies of completed education, grades and other certificates.
Use the button at the foot of the page to reach the application form.
Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered.
Application deadline: 15 July, 2025
For questions, please contact:
Prof. Nikolce Murgovski, Systems and Control
nikolce.murgovski@chalmers.se, +46-31-772-4800
Senior Researcher, Mats Jonasson, Vehicle Engineering and Autonomous Systems
mats.jonasson@chalmers.se, +46-31-772-1373
Researcher Jordanka Kovaceva, Vehicle Safety
jordanka.kovaceva@chalmers.se, +46-31-772-1266
*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***
The research addresses key challenges in motion planning and control under uncertainty, with a particular focus on how to allocate forces and make robust decisions when some vehicle actuators may be partially or fully degraded. You will contribute to both theoretical developments and applied solutions, with a strong emphasis on safety, interpretability, and real-time feasibility.
This is a stimulating position for candidates interested in interpretable AI, formal safety guarantees, and impactful research in sustainable mobility.
Project overview
The position focuses on interpretable, learning-based stochastic optimal control for over-actuated electric vehicles—vehicles with more actuators than degrees of freedom, which enable sophisticated control strategies but also increase system complexity.
Your work will include:
• Developing modular, efficient, and transparent control algorithms.
• Combining model predictive control with learning-based motion prediction under uncertainty.
• Ensuring algorithms can be deployed in real-time settings.
• Contributing to the development of open-source tools.
The project has both a strong theoretical foundation and practical relevance, aiming to deliver robust, explainable control methods that can be applied in real-world scenarios.
As a postdoc, you will also contribute to the academic environment through co-supervision of students, publication of results in high-impact journals and conferences, and participation in national and international research collaborations.
Research environment
You will be based at the Systems and Control Division at Chalmers, which conducts research in modelling, learning, and optimization for systems such as robots, autonomous vehicles, and electromobility solutions. The division offers a rich academic setting with strong expertise in control theory, machine learning, and probability.
You will also collaborate with:
• Vehicle Safety Division, which applies systems engineering and human factors to improve traffic safety. This division is internationally recognized for its work in virtual safety assessment and predictive evaluation of driver behavior and vehicle systems.
• Vehicle Engineering and Autonomous Systems (VEAS) Division, which conducts research in sustainable transportation, including vehicle dynamics, autonomous systems, and energy-efficient mobility solutions.
Together, these divisions create a dynamic and interdisciplinary environment with close ties to industry and society.
Main responsibilities
• Conduct high-quality research in interpretable, learning-based stochastic optimal control.
• Design and implement scalable algorithms for motion planning and control in uncertain environments.
• Collaborate with industry partners to validate methods via simulation and, potentially, real-world prototypes.
• Publish research results and present them at international venues.
• Engage in cross-disciplinary collaborations and contribute to the broader research community at Chalmers.
• Support the supervision of bachelor’s, master’s, and PhD students.
• Contribute to the preparation of research proposals and technical reports.
Your profile
To be eligible for this position, you must have:
• A PhD awarded no more than three years prior to the application deadline, in a relevant subject area such as control systems, robotics, applied mathematics, or machine learning.*
• Strong programming skills and experience with numerical methods and simulation.
• Excellent communication skills in English, both written and spoken.
• Demonstrated ability to work in international and cross-organizational research environments.
*Exceptions to the three-year rule may be granted for documented periods of parental leave, sick leave, or military service. The date on your doctoral certificate will be used to determine eligibility.
Contract terms
This postdoc position is a full-time temporary employment for two to three years.
What we offer
Chalmers provides a cultivating and inspiring working environment in the coastal city of Gothenburg.
Read more about working at Chalmers and our benefits for employees.
Application procedure
The application should be written in English and be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.
CV: (Please name the document as: CV, Surname) including:
• CV, include complete list of publications
• Previous teaching and pedagogical experiences
• Two references that we can contact.
Personal letter: (Please name the document as: Personal letter, Family name)
1-3 pages where you:
• Introduce yourself
• Describe your previous research fields and main research results
• Describe your future goals and future research focus
Other documents:
• Attested copies of completed education, grades and other certificates.
Use the button at the foot of the page to reach the application form.
Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered.
Application deadline: 15 July, 2025
For questions, please contact:
Prof. Nikolce Murgovski, Systems and Control
nikolce.murgovski@chalmers.se, +46-31-772-4800
Senior Researcher, Mats Jonasson, Vehicle Engineering and Autonomous Systems
mats.jonasson@chalmers.se, +46-31-772-1373
Researcher Jordanka Kovaceva, Vehicle Safety
jordanka.kovaceva@chalmers.se, +46-31-772-1266
*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***